app.py

from fastapi import FastAPI, HTTPException
from pydantic import BaseModel
from orator import Session, SQLDatabase, DocumentDatabase
from langchain.chat_models import init_chat_model
from fastapi.responses import StreamingResponse
from fastapi.middleware.cors import CORSMiddleware
import asyncio

# Initialize FastAPI app
app = FastAPI(title="Orator Chat API")

app.add_middleware(
	CORSMiddleware,
	allow_origins=["*"],  # Use a specific origin in production
	allow_credentials=True,
	allow_methods=["*"],  # Allow all methods (GET, POST, etc.)
	allow_headers=["*"],  # Allow all headers
)

# Initialize LLM and databases
llm = init_chat_model("o3-mini", model_provider="openai")
chinook_db = SQLDatabase.from_uri("sqlite:////home/geetu/work/orator/data/chinook/Chinook.db")
pricegram_db = DocumentDatabase("/home/geetu/work/orator/data/pricegram/data.json", top_k=10)

# Initialize session
session = Session(llm=llm, datasources=[chinook_db, pricegram_db])

# Pydantic model for request
class QueryRequest(BaseModel):
	query: str
	source: int


@app.post("/query/")
async def get_response(request: QueryRequest):
	"""Process a query and return the response."""
	try:
		print("Got Request:", request)
		response, logs = session.invoke(request.query, datasource=request.source)
		response = {"response": response}
		print("Sending Respose:", response)
		return response
	except Exception as e:
		raise HTTPException(status_code=500, detail=str(e))


@app.post("/query/stream/")
async def stream_response(request: QueryRequest):
	"""Stream responses for a given query."""
	async def event_generator():
		try:
			events = session.stream(request.query)
			for event in events:
				for person, quote in event.items():
					yield f"{person}: {quote['messages'][-1].text}\n"
					await asyncio.sleep(0.1)  # Simulate streaming delay
		except Exception as e:
			yield f"Error: {str(e)}"

	return StreamingResponse(event_generator(), media_type="text/plain")


@app.get("/")
async def root():
	return {"message": "Welcome to the Orator Chat API"}